Analysis of impact of change in an organizational entity

ABSTRACT

A method and system for analyzing impact of change in an organizational entity. A graph H includes nets, nodes of the nets, edges connecting the nodes, and edge weights for the edges. The edge weights denote changes in some nodes resulting from changes in other nodes. For a given set Z of nodes A and for each node B characterized by a set S of at least one path of edges connecting nodes of H from node A to node B for each node A of Z, a measure M(Z,B) of a change in node B resulting from a change in each node A of Z is determined. M(Z,B) is a function of the edge weights in each path of S. Each node B of H is displayed via a graphical representation G(B) assigned to each node B. G(B) is a function of M(Z,B).

BACKGROUND OF THE INVENTION

1. Technical Field

The present invention relates to a method and system for analyzing animpact of change in an organizational entity.

2. Related Art

Changes within an organizational entity (i.e., a for-profit businessentity, a non-profit business entity, governmental entity, etc.) mayresult from changes elsewhere in the entity, and the resultant changesin the entity may have a significant impact on the organizational entity(e.g., business results for a business entity). However, this impact maybe difficult to analyze if the changes elsewhere in the organizationalentity propagate in a complicated manner through the organizationalentity. Thus there is a need for an organized method of analyzingchanges within an organizational entity resulting from changes elsewherein the organizational entity.

SUMMARY OF THE INVENTION

The present invention provides a method for analyzing an impact ofchange in an organizational entity, said method comprising:

specifying a graph H for the organizational entity, said graph Hcomprising a plurality P of nets, at least two nets of P having uniquesemantics, each net of P comprising a plurality of nodes, each node ineach net of P being directly connected by an edge to at least one othernode in said each net in P, at least one node of each net of P directlyconnected by an edge to at least one node of at least one other net ofP, each edge in H directly connecting a first node and a second nodesuch that said each edge comprises (1) a first edge weight denoting achange in the second node resulting from a change in the first node(e.g., the monetary cost of the task transition associated with theedge, or hierarchical nature of the connection between the two items, orthe time required for the task transition) and (2) a second edge weightdenoting a change in the first node resulting from a change in thesecond node;

for a given set Z of nodes A in H and for each node B characterized by aset S of at least one path of contiguous edges connecting nodes of Hfrom node A to node B for each node A of Z, determining a measure M(Z,B)of a change in node B resulting from a change in each node A of Z, saidM(Z,B) being a function of the edge weights comprised by each contiguousedge in each path of S;

assigning a graphical representation G(B) to said each node B, said G(B)being a function of M(Z,B); and

displaying the graph H such that said each node B is displayed inaccordance with the graphical representation G(B) assigned to said eachnode B.

The present invention provides a computer program product, comprising acomputer usable medium having a computer readable program that whenexecuted on a computer causes the computer to perform a method foranalyzing an impact of change in an organizational entity, said methodcomprising:

specifying a graph H for the organizational entity, said graph Hcomprising a plurality P of nets, at least two nets of P having uniquesemantics, each net of P comprising a plurality of nodes, each node ineach net of P being directly connected by an edge to at least one othernode in said each net in P, at least one node of each net of P directlyconnected by an edge to at least one node of at least one other net ofP, each edge in H directly connecting a first node and a second nodesuch that said each edge comprises (1) a first edge weight denoting achange in the second node resulting from a change in the first node and(2) a second edge weight denoting a change in the first node resultingfrom a change in the second node;

for a given set Z of nodes A in H and for each node B characterized by aset S of at least one path of contiguous edges connecting nodes of Hfrom node A to node B for each node A of Z, determining a measure M(Z,B)of a change in node B resulting from a change in each node A of Z, saidM(Z,B) being a function of the edge weights comprised by each contiguousedge in each path of S;

assigning a graphical representation G(B) to said each node B, said G(B)being a function of M(Z,B); and

displaying the graph H such that said each node B is displayed inaccordance with the graphical representation G(B) assigned to said eachnode B.

The present invention provides a computer system comprising a processorand a computer readable memory unit coupled to the processor, saidmemory unit containing instructions that when executed by the processorimplement a method for analyzing an impact of change in anorganizational entity, said method comprising:

specifying a graph H for the organizational entity, said graph Hcomprising a plurality P of nets, at least two nets of P having uniquesemantics, each net of P comprising a plurality of nodes, each node ineach net of P being directly connected by an edge to at least one othernode in said each net in P, at least one node of each net of P directlyconnected by an edge to at least one node of at least one other net ofP, each edge in H directly connecting a first node and a second nodesuch that said each edge comprises (1) a first edge weight denoting achange in the second node resulting from a change in the first node and(2) a second edge weight denoting a change in the first node resultingfrom a change in the second node;

for a given set Z of nodes A in H and for each node B characterized by aset S of at least one path of contiguous edges connecting nodes of Hfrom node A to node B for each node A of Z, determining a measure M(Z,B)of a change in node B resulting from a change in each node A of Z, saidM(Z,B) being a function of the edge weights comprised by each contiguousedge in each path of S;

assigning a graphical representation G(B) to said each node B, said G(B)being a function of M(Z,B); and

displaying the graph H such that said each node B is displayed inaccordance with the graphical representation G(B) assigned to said eachnode B.

The present invention provides a process for deploying computinginfrastructure, said process comprising integrating computer-readablecode into a computing system, wherein the code in combination with thecomputing system is capable of performing a method for analyzing animpact of change in an organizational entity, said method comprising:

specifying a graph H for the organizational entity, said graph Hcomprising a plurality P of nets, at least two nets of P having uniquesemantics, each net of P comprising a plurality of nodes, each node ineach net of P being directly connected by an edge to at least one othernode in said each net in P, at least one node of each net of P directlyconnected by an edge to at least one node of at least one other net ofP, each edge in H directly connecting a first node and a second nodesuch that said each edge comprises (1) a first edge weight denoting achange in the second node resulting from a change in the first node and(2) a second edge weight denoting a change in the first node resultingfrom a change in the second node;

for a given set Z of nodes A in H and for each node B characterized by aset S of at least one path of contiguous edges connecting nodes of Hfrom node A to node B for each node A of Z, determining a measure M(Z,B)of a change in node B resulting from a change in each node A of Z, saidM(Z,B) being a function of the edge weights comprised by each contiguousedge in each path of S;

assigning a graphical representation G(B) to said each node B, said G(B)being a function of M(Z,B); and

displaying the graph H such that said each node B is displayed inaccordance with the graphical representation G(B) assigned to said eachnode B.

The present invention provides an organized method of analyzing changeswithin an organizational entity resulting from changes elsewhere in theorganizational entity.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a resource net, a capability net, a process net, and arole net of an organizational entity, in accordance with embodiments ofthe present invention.

FIG. 2 depicts a graph comprising the nets of FIG. 1 with indicatededges between the nets, in accordance with embodiments of the presentinvention.

FIG. 3 depicts the graph of FIG. 2 with indicated edge weights, inaccordance with embodiments of the present invention.

FIGS. 4-5 depicts nodes of a graph with different net configurations, inaccordance with embodiments of the present invention.

FIG. 6 depicts the graph of FIGS. 4-5 with added edge weights and thenets deleted for simplicity, in accordance with embodiments of thepresent invention.

FIG. 7 is a table depicting calculation of a measure of change in eachnode of FIG. 6 resulting from a change in one of the nodes of FIG. 6, inaccordance with embodiments of the present invention.

FIG. 8 is a table depicting calculation of a measure of change in eachnode of FIG. 6 resulting from a change in two of the nodes of FIG. 6, inaccordance with embodiments of the present invention.

FIGS. 9-10 depicts the graph of FIG. 6 with each node being marked witha graphical representation to indicate a measure of change in each nodefrom the table of FIG. 7, in accordance with embodiments of the presentinvention.

FIGS. 11-12 depicts the graph of FIG. 6 with each node being marked witha graphical representation to indicate a measure of change in each nodefrom the table of FIG. 8, in accordance with embodiments of the presentinvention.

FIG. 13 is a flow chart for depicting a method for analyzing an impactof change in an organizational entity, in accordance with embodiments ofthe present invention.

FIG. 14 illustrates a computer system used for analyzing an impact ofchange in an organizational entity, in accordance with embodiments ofthe present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention discloses a method and system for an analyzing howa change occurring in one or more aspects of an organizational entityimpacts other aspects of the organizational entity. The presentinvention also discloses how such impacts may be graphicallyrepresented.

An “organizational entity” is any form of organization havingorganizational units (e.g., a business entity, a non-profit entity, agovernmental entity, etc.). Examples of a business entity include: soleproprietorship, general partnership, limited partnership, corporation,limited liability company, limited liability partnership, and a businesscombination. Examples of business combinations include: mergers, jointventures, consolidation, acquisition, strategic alliance, association,etc.

An organizational entity may described in terms of its organizationalunits representing “semantics” of the organizational entity. A“semantics” of an organizational entity is a category or aspect of theorganizational entity. For example, the organizational entity maycomprise four units respectively having a resource semantics, a processsemantics, a capability semantics, and a role semantics.

As will be discussed in detail infra, the semantics of an organizationalentity may be represented graphically in a graph. Each semantics in thegraph is represented by a net comprising interconnected nodes, whereinthe nodes of the net represent the components of the semantics. Thus, aresource semantics is represented as a resource net, a process semanticsis represented as a process net, a capability semantics is representedas a capability net, and a role semantics is represented as a role net.

As an example of said interconnected nodes, each interconnection betweena first node and a second node of the net is represented by a line(called an “edge”) therebetween and two edge weights associated with theedge. The edge represents a coupling between the first and second nodes.A first edge weight of the two edge weights denotes (i.e., serves as anindication of) a change in the second node resulting from a change inthe first node. A second weight of the two edge weights denotes (i.e.,serves as an indication of) a change in the first node resulting from achange in the second node. Thus, a denoted change in a node relating toan edge weight is a value indicative of a change in the node which maybe in some embodiments the value of the change itself, a function of thevalue of the change, a value representing the change, etc. (e.g., themonetary cost of the task transition associated with the edge,hierarchical nature of the connection between the two items, the timerequired for the task transition, etc.).

Nodes of different semantics of the graph may also be connected by edgesand associated edge weights, since nodes of different nets may bemutually coupled and since a change at a node of a first net may resultin a change in a node of a second net.

Resources of a resource semantics are elements (i.e., nodes) in theorganizational entity that may be accessed to provide some functionalityor input required for the execution of an activity. Resources themselvesare not considered to be activities, but rather, passive elements in theorganizational entity. Resources nodes of a resource net may include,inter alia, buildings, vehicles, processing machines, supplies, rawmaterials, subassemblies, software applications, and databases,knowledge repositories, etc. Edge connections are made from the resourcenode that performs the access. For example, an accounting applicationmay access a database. The edge weight of the connection reflects adegree of dependence that one resource has on another insofar as achange in the one resource results in a change in the other resource.Some processes and capabilities may require access to one or moreresources. Connections may be made for each resource required.

Processes of a process semantics comprise time-ordered sequences ofactivities that are executed in the operation of the organizationalentity. Process nodes of a process net may include, inter alia,computing a value, writing a report, displaying an output of acalculation, producing a part of an automobile, etc. Process nets of aprocess semantics, or between two process semantics, may behierarchical; that is, one process in a process net may itself be aprocess net. A node of a process net may represent a process step of theassociated process semantics. Edge connections between nodes of aprocess net represent the sequence of process flow from each node toeach subsequent node and the impact of a change in each process node onthe subsequent nodes of the process. Some processes are bidirectional.For example, it may be possible for process A to transition to processB, and for process B to transition to process A, with consequentialoccurrence of a change in B resulting from a change in A, and a changein A resulting from a change in B. The edge weights of the edges in aprocess net may represent the monetary cost of this step in the processflow, or the complexity of this step in the process flow (e.g., amountof training required).

Capabilities of a capability semantics provide ways of looking at anorganizational entity, (e.g., organizational area such as business area)from the perspective of what the organizational entity is able to do orprovide in the way of useful affordances toward the accomplishment ofdesired results (e.g., business results for a business entity). A resultis something valued by the organizational entity or one of itsstakeholders, and elicits work or other investment in order that such aresult can be realized. A capability represents an ability of theorganizational entity to provide or produce some result (e.g., byperforming an action). A capability net results from analyzingdependencies among various capabilities that have been identified.Capability nodes of a capability net may include, inter alia, acapability of minimizing loan risk, a capability of maintaining clientaccounts, etc. Capabilities are distinguished from processes, in thatprocesses rely on a time-ordered sequence for definition, whereascapabilities have no explicit time sequence and instead facilitatesachievement of a result. If an edge connects an enabled capability andan enabling capability, then an edge weight associated with the edgereflects a degree to which a change in the enabling capability resultsin a change in the enabled capability.

Roles of a role semantics represent roles played by people in theorganizational entity. Edge connections may be made from one role that“reports to” another. For a reporting role that reports to a pluralityof roles, the there will be an edge between the reporting role and eachrole of the plurality of roles. The edge weights of an edge within arole net, or between two role nets, indicates a degree of change in eachsaid role node due to a change in the other said role net. For example,consider a reporting relationship of an auditor to his/her personnelmanager and to his/her team leader in a matrix organization. Thepersonnel manager may only affect the auditor in personnel reviews andpromotions, whereas the team leader may be required to authorize alltransactions. This would give the personnel manager a relatively weakedge connection which is reflected in the associated edge weight, andthe team leader a stronger connection which is likewise reflected in theassociated edge weight. Role nodes of a role net may include, interalia, a supervisor, a loan officer, an auditor, an actuary, etc.

While the preceding discussion described one net of each semantics, eachsemantics generally comprises one or more nets. For example a givensemantics of the organizational entity may consist of exactly one net ofinterconnected nodes. Alternatively, the given semantics of theorganizational entity may comprise a plurality of nets such that a nodeof a first net of the plurality of nets is connected to a node of atleast one other net, wherein the at least one other net is a second netof the plurality of nets, a net of another semantics of theorganizational entity, or a combination thereof.

FIG. 1 depicts a resource net 100, a capability net 200, a process net300, and a role net 400 of an organizational entity, in accordance withembodiments of the present invention.

The resource net 100 comprises a network server node 101, an auditingapplication node 102, and a client database node 103. Nodes 101 and 102are coupled by edge 1112. Nodes 102 and 103 are coupled by edge 1213.Nodes 101 and 103 are coupled by edge 1113.

The capability net 200 comprises an account maintenance node 201, a loanrisk minimization node 202, and a reserves reduction node 203. Nodes 201and 202 are coupled by edge 2122. Nodes 202 and 203 are coupled by edge2223.

The process net 300 comprises a populating daily activities reports node301, a logging errors node 302, a receiving weekly market data node 303,and a sending reports to data entry node 304. Nodes 301 and 302 arecoupled by edge 3132. Nodes 301 and 303 are coupled by edge 3133. Nodes303 and 304 are coupled by edge 3334.

The role net 400 comprises a supervisor node 401, an auditor node 402, aloan officer node 403, and an actuary node 404. Nodes 401 and 402 arecoupled by edge 4142. Nodes 401 and 403 are coupled by edge 4133. Nodes401 and 404 are coupled by edge 4144. Nodes 402 and 403 are coupled byedge 4243.

FIG. 2 depicts a graph comprising the nets of FIG. 1 with indicatededges between the nets, in accordance with embodiments of the presentinvention. Node 103 of the resource net and node 301 of the process netare coupled by edge 1331. Node 103 of the resource net and node 302 ofthe process net are coupled by edge 1332. Node 103 of the resource netand node 201 of the capability net are coupled by edge 1321. Node 203 ofthe capability net and node 302 of the process net are coupled by edge2332. Node 203 of the capability net and node 402 of the role net arecoupled by edge 2342. Node 202 of the capability net and node 404 of therole net are coupled by edge 2244.

FIG. 3 depicts the graph of FIG. 2 with indicated edge weights, inaccordance with embodiments of the present invention. Although each edgehas two edge weights, only non-zero edge weights are actually shown inFIG. 3. Thus the edges in FIG. 3 for which only one edge weight is shownimplies that the edge weight that is not shown for the edge is zero.Each edge weight is shown as a vector with an associated weight value,wherein the weight value for an edge weight pointing from a first nodeto a second node denotes the change in the second node resulting from achange in the first node, as illustrated by a few examples.

The edge weight 1113 points from node 101 to node 103 and has a weightvalue of 0.59, which means that 0.59 denotes a change in node 103resulting from a change in node 101.

The edge weight 2342 points from node 402 to node 203 and has a weightvalue of 0.11, which means that 0.11 denotes a change in node 203resulting from a change in node 402.

Two edge weights are shown for edge 1112. The first edge weight for edge1112 points from node 101 to node 102 and has a weight value of 0.40,which means that 0.40 denotes a change in node 102 resulting from achange in node 101. The second edge weight for edge 1112 points fromnode 102 to node 101 and has a weight value of 0.20, which means that0.20 denotes a change in node 101 resulting from a change in node 102.Note that node 101 has twice the effect on node 102 that node 102 has onnode 101 (i.e., 0.40/0.20=2), which illustrates that the two edgeweights for an edge may have different values.

Two edge weights are shown for edge 1321. The first edge weight for edge1321 points from node 103 to node 201 and has a weight value of 0.30,which means that 0.30 denotes a change in node 201 resulting from achange in node 103. The second edge weight for edge 1321 points fromnode 201 to node 103 and has a weight value of 0.30, which means that0.30 denotes a change in node 103 resulting from a change in node 201.Note that nodes 103 and 201 have the same effect on each other (i.e.,0.30/0.30=1), which illustrates that the two edge weights for an edgemay have the same value.

The significance of the edge weights depends on the relative magnitudeof the edge weights with respect to one another as distributedthroughout the graph. Assigning the two edge weights for an edge betweentwo nodes, node 1 and node 2, is context dependent in consideration ofthe nets that comprise nodes 1 and 2, and of the manner in which nodes 1and 2 interact with each other. For example with respect to the auditingapplication 102 and the network server 101 of FIG. 1, if the auditingapplication 102 is enhanced to include calculations that are classifiedat a higher security level than can be accommodated by the networkserver 101, then the network server 101 must be consequently upgraded toaccommodate the new higher security level, which may increase costand/or manpower, resulting in a weight that is reflective of saidincreased cost and/or manpower. As another example, if the supervisor401 in the role net of FIG. 1 is replaced by another supervisor ofincreased training and knowledge, the auditor 402, loan officer 403, andactuary 404 may each have their performance improved to an extent thattheir performance is positively affected by the training and knowledgeof the supervisor 401, and the associated edge weights may reflect amonetary equivalent of their improved performance. In one embodiment, anedge weight W(1,2) denoting a change (D2) in node 2 resulting from achange (D 1) in node 1 may be a function of the partial derivative∂(D2)/∂(D1).

FIGS. 4-5 depict nodes 1-6 of a graph with different net configurations,in accordance with embodiments of the present invention. Nodes 1 and 2are coupled by edge 12. Nodes 2 and 3 are coupled by edge 23. Nodes 3and 4 are coupled by edge 34. Nodes 4 and 5 are coupled by edge 45.Nodes 5 and 6 are coupled by edge 56. Nodes 2 and 5 are coupled by edge25. Nodes 1 and 6 are not directly coupled. In FIG. 4, net 71 comprisesnodes 1 and 2, net 72 comprises nodes 3 and 4, and net 73 comprisesnodes 5 and 6. In FIG. 5, net 72 comprises nodes 3 and 4 (as in FIG. 4)and net 74 comprises nodes 1, 2, 5, and 6. Nets 71 and 72 of FIG. 4 eachhave the same semantics. Nets 73 of FIG. 4 and net 74 of FIG. 5 eachhave a semantics that differs from the semantics of nets 71 and 72.

FIG. 6 depicts the graph of FIGS. 4-5 with added edge weights and thenet indications deleted for simplicity, in accordance with embodimentsof the present invention. Two non-zero edge weights are shown for eachedge, indicating that the each node of the two nodes connected by eachedge are changed as a result of a change in the other node of the twoconnected nodes. For example for edge 34 connecting nodes 3 and 4, afirst edge weight of 0.60 denotes a change in node 4 resulting from achange in node 3, and a second edge weight of 0.50 denotes a change innode 3 resulting from a change in node 4.

If a change occurs in node 1 each node in the graph of FIG. 6 isimpacted by a corresponding change in accordance with the edge weightsshown in FIG. 6. For example, the effect of a change in node 5 resultingfrom a change in node 1 may be determined by considering all relevantpaths from node 1 to node 5. For each such relevant path, each edge inthe relevant path has a non-zero edge weight that points in a directionfrom node 1 to node 5. FIG. 6 shows two such paths, namely 1-2-5 and1-2-3-4-5. The path length of a path from node 1 to node 5 is defined asa function of the edge weights of the edges along the path for the edgeweights pointing from node 1 to node 5 (e.g., the product or sum of theedge weights of the edges along the path for edge weights pointing fromnode 1 to node 5). The examples presented herein calculate the pathlength as the product of the successive edge weights along the path forillustrative purpose only, recognizing that other functions of the edgeweights may be employed such as a weighted or unweighted sum of the edgeweights along the path or other functional forms.

Accordingly, for the path 1-2-5, the path length is 0.7*0.5=0.35. Forthe path 1-2-3-4-5, the path length is 0.7*0.2*0.6*0.9=0.076. A measureM(1,5) of the change in node 5 resulting from a change in node 1 is afunction of the computed path lengths of the paths from node 1 to node5. In one embodiment, M(1,5) is the maximum path length of 0.35 since0.35 is the maximum of 0.35 and 0.076. In one embodiment, M(1,5) is anunweighted sum (0.426) the path lengths, since the sum of 0.35 and 0.076is 0.426. In one embodiment, each path is assigned a path weight andM(1,5) is the weighted sum of the path lengths. For example, if the pathweights for the paths 1-2-5 and 1-2-3-4-5 are 0.25 and 0.75,respectively, then M(1,5) is 0.25*0.35+0.75*0.076=0.144.

FIG. 7 is a table depicting calculation of a measure of change M(1,n) ineach node n (n=1, 2, 3, 4, 5, 6) of FIG. 6 resulting from a change innode 1 of FIG. 6, in accordance with embodiments of the presentinvention. For values of n other than n=5, the measure M(1,n) has beencomputed in fashion similar to the computation of M(1,5) describedsupra. FIG. 7 includes two measures of M(1,n), namely the maximum pathlength and the unweighted sum of path lengths. A weighted sum of pathlengths could also have been included in FIG. 7, by following theexample described supra for computing a weighted sum of path lengths forM(1,5).

For a given node n, use of the maximum path length for the measureM(1,n) represents embodiments in which only the most importantcontributing path from node 1 to node n is used to model M(1,n). Use ofthe unweighted sum of path lengths for the measure M(1,n) representsembodiments which reflect the collective effect on M(1,n) of the mostimportant contributing path and of other contributing paths from node 1to node n.

Only “non-inclusive paths” (i.e., those paths not wholly included withinother paths) are shown in the table of FIG. 7. For example for impactednode 2, only path 1-2 is shown. For example, a path not shown forimpacted node 2 is 1-2-3-4-5-2, because path 1-2 is wholly includedwithin path 1-2-3-4-5-2. In actuality, there are an infinite number ofsuch “inclusive paths” from node 1 to node 2 from looping around path2-3-4-5-2 an arbitrary number of times. The set of such inclusive pathsnot included in Table 7 are: 1-2-[3-4-5-2]_(R), where R denotes Rrepetitions of sub-path [3-4-5-2], R being any positive integer. Inprinciple, the non-inclusive paths contribute to the measure M(1,n), butsuch contributions may be neglected in cases where such contributionsare negligible. In cases where non-inclusive paths to the measure M(1,n)are accounted for, the effect of the non-inclusive paths may be modeledby appropriate mathematical or numerical techniques such by a geometricseries model of the successive non-inclusive paths (i.e., for R=1, 2, 3,. . . ).

In the table of FIG. 7, node 1 may be viewed as a “source node” forinducing change in the other nodes. Interestingly, the initial change inthe source node 1 that results in the changes in the other nodesactually feeds back to node 1 as an additional change in node 1, due tofeedback from the changes in the other nodes. The feedback paths to node1 are paths 1-2-3-4-5-2-1 and 1-2-5-4-3-2-1, as indicated in FIG. 7 andas may be verified from inspection of FIG. 6. The feedback effect onnode 1 is relatively small, however, with a maximum path length of only0.022 and an unweighted sum of path lengths of only 0.037.

In general, a measure M(N1,N2) of a change in a node N2 resulting from achange in node N1 is a function F of the path lengths of the paths fromN1 to N2. The path length of each path is the product the pertinent edgeweights (as illustrated in the preceding example) of the contiguousedges along each such path. In one embodiment, the function F maycomprise maximum path length of said path lengths. In one embodiment,the function F may comprise an unweighted sum of said path lengths. Inone embodiment, the function F may comprise a weighted sum of said pathlengths.

FIG. 8 is a table depicting calculation of a measure of change M(1:6,n)in each node (n=1, 2, 3, 4, 5, 6) of FIG. 6 resulting from a change innodes 1 and 6 of FIG. 6, in accordance with embodiments of the presentinvention. With both paths 1 and 6 affecting the measure M(1:6,n), acomparison of FIGS. 7 and 8 shows that M(1:6,n) exceeds M(1,n) for eachindicated measure embodiment (i.e., maximum path length, unweighted sumof path lengths).

In the table of FIG. 8, nodes 1 and 6 may be viewed as a set of “sourcenodes” for inducing change in the other nodes. For the netconfigurations of FIGS. 4 and 5, the source nodes 1 and 6 are indifferent nets 71 and 73 in FIG. 4, and in a same net 74 in FIG. 5. Ingeneral, the source nodes of a set of sources nodes may include one ormore source nodes (e.g., a single source node, a plurality of sourcenodes, etc.) such that the source nodes are in a same net, the sourcenodes are distributed among a plurality of nets of a same semantics, orthe source nodes are distributed among a plurality of nets wherein atleast two of nets of the plurality of nets have a different semantics.

Although the examples illustrated in FIGS. 7 and 8 employ a maximum pathlength and an unweighted sum of path lengths to model the measure M, theinvention may generally utilize any other relevant function of the pathlengths to model M (e.g., weighted sum of path lengths, product of pathlengths or other nonlinear functions of path lengths, arithmetic averageof path lengths, etc.). The context of the application to which theinvention is applied will govern which functions of the path lengths maybe beneficially utilized.

FIGS. 9-10 depicts the graph of FIG. 6 with each node n (n=1, 2, 3, 4,5, 6) being marked with a graphical representation G(n) to indicate themeasure M of change in each node from the table of FIG. 7, in accordancewith embodiments of the present invention. In FIGS. 9-10, G(n) isexpressed as a function of M, wherein shades of grey denote ranges of M.

In FIG. 9, the legend indicates that the three shades of greyrepresenting G(n) denote the following ranges of M, wherein M representsthe maximum path length:

M>0.5 (Darkest shade of grey);

0.2≦M≦5 (Medium shade of grey);

M<0.2 (Lightest shade of grey—white).

In FIG. 10, the legend indicates that the three shades of greyrepresenting G(n) denote the following ranges of M, wherein M representsthe unweighted sum of path lengths:

M>0.75 (Darkest shade of grey);

0.3≦M≦75 (Medium shade of grey);

M<0.3 (Lightest shade of grey—white).

FIGS. 11-12 depicts the graph of FIG. 6 with each node n (n=1, 2, 3, 4,5, 6) being marked with a graphical representation G(n) to indicate themeasure M of change in each node from the table of FIG. 8, in accordancewith embodiments of the present invention. In FIGS. 11-12, G(n) isexpressed as a function of M, wherein shades of grey denote ranges of M.

In FIG. 11, the legend indicates that the three shades of greyrepresenting G(n) denote the following ranges of M, wherein M representsthe maximum path length:

M>0.6 (Darkest shade of grey);

0.25≦M≦6 (Medium shade of grey);

M<0.25 (Lightest shade of grey—white).

In FIG. 12, the legend indicates that the three shades of greyrepresenting G(n) denote the following ranges of M, wherein M representsthe unweighted sum of path lengths:

M>1.2 (Darkest shade of grey);

0.5≦M≦0.2 (Medium shade of grey);

M<0.5 (Lightest shade of grey—white).

Although FIGS. 9-12 use three shades of grey to differentiate differentranges of M for each node, the present invention generally utilizes twoor more shades of grey to differentiate different ranges of M for eachnode. The shades of grey may increase in darkness as M increases (as inFIGS. 9-12), may alternatively decrease in darkness as M increases, orvary with darkness in any other manner.

More generally, FIGS. 9-12 illustrate that the present invention definesranges of measure of a change one node resulting from a change in one ormore other nodes, wherein the graphical representation G representingthe change in the one node is specific to a range that includes M.

Moreover, the graphical representation G(n) may be expressed as afunction of M in other nodes than shades of grey. In one embodiment,G(n) may be an icon. In one embodiment, the graphical representationG(n) may be a spectral color that is visible to a human being. Thewavelength s(M) associated with the spectral color may be amonotonically increasing or decreasing function of M, wherein s(M) maybe a linear or non-linear function of M Alternatively, the spectralcolor may vary with M in a manner other than monotonically increasing ordecreasing, such as the “heat map” color usage, with red denoting highvalue and transitioning by approximate wavelength of color to bluedenoting low numbers.

FIG. 13 is a flow chart for depicting steps 81-85 a method for analyzingan impact of change in an organizational entity, in accordance withembodiments of the present invention.

Step 81 specifies nodes, edges, and edge weights of a graph H for anorganizational entity. The graph H comprises a plurality P of nets. Atleast two nets of P have unique semantics. Each net of P comprises aplurality of nodes. Each node in each net of P is directly connected byan edge to at least one other node in each net in P. At least one nodeof each net of P is directly connected by an edge to at least one nodeof at least one other net of P. Each edge in H directly connects a firstnode and a second node such that said each edge comprises: (1) a firstedge weight denoting a change in the second node resulting from a changein the first node and (2) a second edge weight denoting a change in thefirst node resulting from a change in the second node.

Step 82 specifies a set Z of source nodes A for inducing change in othernodes of the graph H.

Step 83 determines a measure of change in the remaining nodes of H dueto change in the source nodes A of Z. Given the specified source nodes Ain Z in a net X of P and for each node B characterized by a set S of atleast one path of contiguous edges connecting nodes of H from node A tonode B for each node A of Z, step 83 determines a measure M(Z,B) of achange in B resulting from a change in each node A of Z. M(Z,B) is afunction of the edge weights comprised by each contiguous edge in eachpath of S. The first and second edge weights of a contiguous edge of apath of S: may be equal, may be unequal, may be zero and positiverespectively, etc.

In one embodiment, a node of said each node B may be in a net Y of Pthat differs from the net X, wherein the nets X and Y have a samesemantics. In one embodiment, a node of said each node B may be in a netY of P that differs from the net X, wherein the nets X and Y havedifferent semantics. In one embodiment, a node of said each node B is ina net Y of P, wherein G(B) is a function of M(Z,B) and Y.

The measure M(Z,B) may be determined by: computing a path length of eachpath of S; and determining M(Z,B) as a function of the computed pathlengths. Each path of S may be computed as a product of the first orsecond edge weight of each contiguous edge of each path of S. In oneembodiment, the computed path lengths may be a maximum path length ofthe computed path lengths. In one embodiment, the computed path lengthsmay be an unweighted sum of the computed path lengths. In oneembodiment, the computed path lengths may be a weighted sum of thecomputed path lengths.

Step 84 assigns a graphical representation G(B) to said each node B,wherein G(B) is a function of M(Z,B).

Step 85 displays the graph H such that said each node B is displayed inaccordance with the graphical representation G(B) assigned to each nodeB. G(B) may be, inter alia, an icon, a color, a shade of grey, etc. Forexample, G(B) may be a shade of grey that is a monotonically increasingor decreasing function of M(Z,B). In addition, ranges of measure of achange in B resulting from a change in A may be specified, wherein G(B)is specific to a range of said ranges that includes M(Z,B).

G(B) may be a spectral color that is visible to a human being. Awavelength s(M,B) of the spectral color for G(B) may be a monotonicallyincreasing or decreasing function of M(Z,B). The wavelength s(M,B) maybe a linear or non-linear function of M(Z,B).

FIG. 14 illustrates a computer system 90 used for analyzing an impact ofchange in an organizational entity, in accordance with embodiments ofthe present invention. The computer system 90 comprises a processor 91,an input device 92 coupled to the processor 91, an output device 93coupled to the processor 91, and memory devices 94 and 95 each coupledto the processor 91. The input device 92 may be, inter alia, a keyboard,a mouse, etc. The output device 93 may be, inter alia, a printer, aplotter, a computer screen, a magnetic tape, a removable hard disk, afloppy disk, etc. The memory devices 94 and 95 may be, inter alia, ahard disk, a floppy disk, a magnetic tape, an optical storage such as acompact disc (CD) or a digital video disc (DVD), a dynamic random accessmemory (DRAM), a read-only memory (ROM), etc. The memory device 95includes a computer code 97 which is a computer program that comprisescomputer-executable instructions. The computer code 97 includes analgorithm for analyzing an impact of change in an organizational entity.The processor 91 executes the computer code 97. The memory device 94includes input data 96. The input data 96 includes input required by thecomputer code 97. The output device 93 displays output from the computercode 97. Either or both memory devices 94 and 95 (or one or moreadditional memory devices not shown in FIG. 14) may be used as acomputer usable medium (or a computer readable medium or a programstorage device) having a computer readable program code embodied thereinand/or having other data stored therein, wherein the computer readableprogram code comprises the computer code 97. Generally, a computerprogram product (or, alternatively, an article of manufacture) of thecomputer system 90 may comprise said computer usable medium (or saidprogram storage device).

While FIG. 14 shows the computer system 90 as a particular configurationof hardware and software, any configuration of hardware and software, aswould be known to a person of ordinary skill in the art, may be utilizedfor the purposes stated supra in conjunction with the particularcomputer system 90 of FIG. 14. For example, the memory devices 94 and 95may be portions of a single memory device rather than separate memorydevices.

While embodiments of the present invention have been described hereinfor purposes of illustration, many modifications and changes will becomeapparent to those skilled in the art. Accordingly, the appended claimsare intended to encompass all such modifications and changes as fallwithin the true spirit and scope of this invention.

1. A computerized method for analyzing an impact of change in anorganizational entity, said method comprising: specifying a graph H forthe organizational entity, said graph H comprising a plurality P ofnets, at least two nets of P having unique semantics, each net of Pcomprising a plurality of nodes, each node in each net of P beingdirectly connected by an edge to at least one other node in said eachnet in P, at least one node of each net of P directly connected by anedge to at least one node of at least one other net of P, each edge in Hdirectly connecting a first node and a second node such that said eachedge comprises (1) a first edge weight denoting a change in the secondnode resulting from a change in the first node and (2) a second edgeweight denoting a change in the first node resulting from a change inthe second node; for a given set Z of nodes A in H and for each node Bcharacterized by a set S of at least one path of contiguous edgesconnecting nodes of H from node A to node B for each node A of Z,determining a measure M(Z,B) of a change in node B resulting from achange in each node A of Z, said M(Z,B) being a function of the edgeweights comprised by each contiguous edge in each path of S; assigning agraphical representation G(B) to said each node B, said G(B) being afunction of M(Z,B); and displaying the graph H such that said each nodeB is displayed in accordance with the graphical representation G(B)assigned to said each node B.
 2. The method of claim 1, whereindetermining the measure M(Z,B) comprises: computing a path length ofeach path of S; and determining M(Z,B) as a function of said computedpath lengths.
 3. The method of claim 2, wherein said computing the pathlength of each path of S comprises computing the path length of eachpath of S as a product of the successive first edge weights or of thesuccessive second edge weights of the contiguous edges along said eachpath of S.
 4. The method of claim 2, wherein said function of saidcomputed path lengths is a maximum path length of said computed pathlengths.
 5. The method of claim 2, wherein said function of saidcomputed path lengths is a weighted or unweighted sum of said computedpath lengths.
 6. The method of claim 1, wherein a node of said nodes Ais in a net X of P, wherein a node of said each node B is in a net Y ofP that differs from the net X, and wherein the nets X and Y havedifferent semantics.
 7. The method of claim 1, wherein G(B) is an icon,a color, or a shade of grey.
 8. The method of claim 1, wherein theplurality of nets consists of a resource net, a capability net, aprocess net, and a role net.
 9. A computer program product, comprising acomputer usable medium having a computer readable program that whenexecuted on a computer causes the computer to perform a method foranalyzing an impact of change in an organizational entity, said methodcomprising: specifying a graph H for the organizational entity, saidgraph H comprising a plurality P of nets, at least two nets of P havingunique semantics, each net of P comprising a plurality of nodes, eachnode in each net of P being directly connected by an edge to at leastone other node in said each net in P, at least one node of each net of Pdirectly connected by an edge to at least one node of at least one othernet of P, each edge in H directly connecting a first node and a secondnode such that said each edge comprises (1) a first edge weight denotinga change in the second node resulting from a change in the first nodeand (2) a second edge weight denoting a change in the first noderesulting from a change in the second node; for a given set Z of nodes Ain H and for each node B characterized by a set S of at least one pathof contiguous edges connecting nodes of H from node A to node B for eachnode A of Z, determining a measure M(Z,B) of a change in node Bresulting from a change in each node A of Z, said M(Z,B) being afunction of the edge weights comprised by each contiguous edge in eachpath of S; assigning a graphical representation G(B) to said each nodeB, said G(B) being a function of M(Z,B); and displaying the graph H suchthat said each node B is displayed in accordance with the graphicalrepresentation G(B) assigned to said each node B.
 10. The computerprogram product of claim 9, wherein determining the measure M(Z,B)comprises: computing a path length of each path of S; and determiningM(Z,B) as a function of said computed path lengths.
 11. The computerprogram product of claim 10, wherein said computing the path length ofeach path of S comprises computing the path length of each path of S asa product of the successive first edge weights or of the successivesecond edge weights of the contiguous edges along said each path of S.12. The computer program product of claim 9, wherein G(B) is an icon, acolor, or a shade of grey.
 13. A computer system comprising a processorand a computer readable memory unit coupled to the processor, saidmemory unit containing instructions that when executed by the processorimplement a method for analyzing an impact of change in anorganizational entity, said method comprising: specifying a graph H forthe organizational entity, said graph H comprising a plurality P ofnets, at least two nets of P having unique semantics, each net of Pcomprising a plurality of nodes, each node in each net of P beingdirectly connected by an edge to at least one other node in said eachnet in P, at least one node of each net of P directly connected by anedge to at least one node of at least one other net of P, each edge in Hdirectly connecting a first node and a second node such that said eachedge comprises (1) a first edge weight denoting a change in the secondnode resulting from a change in the first node and (2) a second edgeweight denoting a change in the first node resulting from a change inthe second node; for a given set Z of nodes A in H and for each node Bcharacterized by a set S of at least one path of contiguous edgesconnecting nodes of H from node A to node B for each node A of Z,determining a measure M(Z,B) of a change in node B resulting from achange in each node A of Z, said M(Z,B) being a function of the edgeweights comprised by each contiguous edge in each path of S; assigning agraphical representation G(B) to said each node B, said G(B) being afunction of M(Z,B); and displaying the graph H such that said each nodeB is displayed in accordance with the graphical representation G(B)assigned to said each node B.
 14. The computer system of claim 13,wherein determining the measure M(Z,B) comprises: computing a pathlength of each path of S; and determining M(Z,B) as a function of saidcomputed path lengths.
 15. The computer system of claim 14, wherein saidcomputing the path length of each path of S comprises computing the pathlength of each path of S as a product of the successive first edgeweights or of the successive second edge weights of the contiguous edgesalong said each path of S.
 16. The computer system of claim 13, whereinG(B) is an icon, a color, or a shade of grey.
 17. A process fordeploying computing infrastructure, said process comprising integratingcomputer-readable code into a computing system, wherein the code incombination with the computing system is capable of performing a methodfor analyzing an impact of change in an organizational entity, saidmethod comprising: specifying a graph H for the organizational entity,said graph H comprising a plurality P of nets, at least two nets of Phaving unique semantics, each net of P comprising a plurality of nodes,each node in each net of P being directly connected by an edge to atleast one other node in said each net in P, at least one node of eachnet of P directly connected by an edge to at least one node of at leastone other net of P, each edge in H directly connecting a first node anda second node such that said each edge comprises (1) a first edge weightdenoting a change in the second node resulting from a change in thefirst node and (2) a second edge weight denoting a change in the firstnode resulting from a change in the second node; for a given set Z ofnodes A in H and for each node B characterized by a set S of at leastone path of contiguous edges connecting nodes of H from node A to node Bfor each node A of Z, determining a measure M(Z,B) of a change in node Bresulting from a change in each node A of Z, said M(Z,B) being afunction of the edge weights comprised by each contiguous edge in eachpath of S; assigning a graphical representation G(B) to said each nodeB, said G(B) being a function of M(Z,B); and displaying the graph H suchthat said each node B is displayed in accordance with the graphicalrepresentation G(B) assigned to said each node B.
 18. The process ofclaim 17, wherein determining the measure M(Z,B) comprises: computing apath length of each path of S; and determining M(Z,B) as a function ofsaid computed path lengths.
 19. The process of claim 18, wherein saidcomputing the path length of each path of S comprises computing the pathlength of each path of S as a product of the successive first edgeweights or of the successive second edge weights of the contiguous edgesalong said each path of S.
 20. The process of claim 17, wherein G(B) isan icon, a color, or a shade of grey.